English

Accurate Indoor Localization Using Acoustic Direction Finding via Smart Phones

Networking and Internet Architecture 2013-06-10 v1

Abstract

We propose and implement a novel indoor localization scheme, Swadloon, built upon an accurate acoustic direction finding. Swadloon leverages sensors of the smartphone without the requirement of any specialized devices. The scheme Swadloon does not rely on any fingerprints and is very easy to use: a user only needs to shake the phone for a short duration before walking and localization. Our Swadloon design exploits a key observation: the relative shift and velocity of the phone-shaking movement corresponds to the subtle phase and frequency shift of the Doppler effects experienced in the received acoustic signal by the phone. A novel method is designed to derive the direction from the phone to the acoustic source by combining the velocity calculated from the subtle Doppler shift with the one from the inertial sensors of the phone. Then a real-time precise localization and tracking is enabled by using a few anchor speakers with known locations. Major challenges in implementing Swadloon are to measure the frequency shift precisely and to estimate the shaking velocity accurately when the speed of phone-shaking is low and changes arbitrarily. We propose rigorous methods to address these challenges, then design and deploy Swadloon in several floors of an indoor building each with area about 2000m^2. Our extensive experiments show that the mean error of direction finding is around 2.1 degree when the acoustic source is within the range of 32m. For indoor localization, the 90-percentile errors are under 0.92m, while the maximum error is 1.73m and the mean is about 0.5m. For real-time tracking, the errors are within 0.4m for walks of 51m.

Keywords

Cite

@article{arxiv.1306.1651,
  title  = {Accurate Indoor Localization Using Acoustic Direction Finding via Smart Phones},
  author = {Wenchao Huang and Yan Xiong and Xiang-Yang Li and Hao Lin and Xufei Mao and Panlong Yang and Yunhao Liu},
  journal= {arXiv preprint arXiv:1306.1651},
  year   = {2013}
}

Comments

Under submission

R2 v1 2026-06-22T00:29:44.328Z